Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use

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dc.contributor.author CHD Exome Consortium
dc.contributor.author Consortium Genetics Smoking
dc.contributor.author EPIC-CVD Consortium
dc.contributor.author Understanding Soc Sci Grp
dc.contributor.author Brazel, David M.
dc.contributor.author Jiang, Yu
dc.contributor.author Hughey, Jordan M.
dc.contributor.author Loukola, Anu
dc.contributor.author Qaiser, Beenish
dc.contributor.author Kaprio, Jaakko
dc.contributor.author Kontto, Jukka
dc.contributor.author Perola, Markus
dc.contributor.author Dunning, Alison M.
dc.date.accessioned 2020-03-05T03:23:30Z
dc.date.available 2021-12-18T03:45:34Z
dc.date.issued 2019-06-01
dc.identifier.citation CHD Exome Consortium , Consortium Genetics Smoking , EPIC-CVD Consortium , Understanding Soc Sci Grp , Brazel , D M , Jiang , Y , Hughey , J M , Loukola , A , Qaiser , B , Kaprio , J , Kontto , J , Perola , M & Dunning , A M 2019 , ' Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use ' , Biological Psychiatry , vol. 85 , no. 11 , pp. 946-955 . https://doi.org/10.1016/j.biopsych.2018.11.024
dc.identifier.other PURE: 125875997
dc.identifier.other PURE UUID: 5797f3c3-c257-4bb6-883d-551382c7631c
dc.identifier.other WOS: 000469962800015
dc.identifier.other ORCID: /0000-0003-0542-5967/work/60161136
dc.identifier.uri http://hdl.handle.net/10138/312902
dc.description.abstract BACKGROUND: Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences and to contribute to disease risk. METHODS: We analyzed similar to 250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack-years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss-of-function coding variants. We performed a novel fine-mapping analysis to winnow the number of putative causal variants within associated loci. RESULTS: Meta-analytic sample sizes ranged from 152,348 to 433,216, depending on the phenotype. Rare coding variation explained 1.1% to 2.2% of phenotypic variance, reflecting 11% to 18% of the total single nucleotide polymorphism heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between three and 10 variants for 65 loci. Twenty loci contained rare coding variants in the 95% credible intervals. CONCLUSIONS: Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior. en
dc.format.extent 10
dc.language.iso eng
dc.relation.ispartof Biological Psychiatry
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject Alcohol
dc.subject Behavioral genetics
dc.subject GWAS
dc.subject Heritability
dc.subject Nicotine
dc.subject Tobacco
dc.subject LOW-FREQUENCY
dc.subject NICOTINE
dc.subject ASSOCIATION
dc.subject DEPENDENCE
dc.subject COMMON
dc.subject ADH1B
dc.subject RISK
dc.subject 3112 Neurosciences
dc.subject 3124 Neurology and psychiatry
dc.title Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use en
dc.type Article
dc.contributor.organization HUSLAB
dc.contributor.organization Institute for Molecular Medicine Finland
dc.contributor.organization Department of Public Health
dc.contributor.organization Genetic Epidemiology
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.1016/j.biopsych.2018.11.024
dc.relation.issn 0006-3223
dc.rights.accesslevel openAccess
dc.type.version publishedVersion
dc.type.version draft

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